科技创新与应用2026，Vol.16Issue(4)：53-57,5.DOI:10.19981/j.CN23-1581/G3.2026.04.012
基于SVM与贝叶斯网络的乡村污水态势预测模型
摘要
Abstract
Aiming at the challenges of data sparsity,multi-source parameter coupling,and dynamic uncertainties in rural sewage management,this paper proposes a hybrid predictive model synergizing Support Vector Machine(SVM)and Bayesian Network.The model employs SVM to achieve high-precision classification of sewage contamination categories,and integrates Bayesian Network for probabilistic inference on multi-factor interactions,thereby constructing a dynamic situation prediction framework of sewage,which provides method support for rural water environment risk early warning and precise treatment.关键词
污水态势预测/支持向量机/贝叶斯网络/概率推理/多源数据融合Key words
sewage situation prediction/support vector machine(SVM)/Bayesian network/probabilistic inference/multi-source data fusion分类
资源环境引用本文复制引用
王宇,胡瀜桓,徐嘉,林家豪,谭欣,罗超良..基于SVM与贝叶斯网络的乡村污水态势预测模型[J].科技创新与应用,2026,16(4):53-57,5.基金项目
国家级大学生创新创业训练计划项目(S202411535046) （S202411535046）
湖南省大学生创新创业训练计划项目(3661) （3661）
